scholarly journals A Tutorial on Fingerprint Recognition

2005 ◽  
pp. 43-68 ◽  
Author(s):  
Davide Maltoni
Keyword(s):  
Fingerprint Recognition

Analysis of Fingerprint Recognition System Using Neural Network

2020 ◽  
Author(s):  
Ganesh Awasthi ◽  
Dr. Hanumant Fadewar ◽  
Almas Siddiqui ◽  
Bharatratna P. Gaikwad
Keyword(s):  
Neural Network ◽  
Recognition System ◽  
Fingerprint Recognition

Evaluation of the effectiveness of different image skeletonization methods in biometric security systems

2020 ◽  
Vol 10 ◽  
Author(s):  
Mariya Nazarkevych ◽  
Serhii Dmytruk ◽  
Volodymyr Hrytsyk ◽  
Olha Vozna ◽  
Anzhela Kuza ◽  
...  
Keyword(s):  
Experimental Studies ◽  
Fingerprint Recognition ◽  
Good Time ◽  
Gabor Filtering ◽  
Security Systems ◽  
Thinning Algorithm ◽  
Biometric Security ◽  
Recognition Quality ◽  
Control And Management ◽  
The Internet Of Things

Background: Systems of the Internet of Things are actively implementing biometric systems. For fast and high-quality recognition in sensory biometric control and management systems, skeletonization methods are used at the stage of fingerprint recognition. The analysis of the known skeletonization methods of Zhang-Suen, Hilditch, Ateb-Gabor with the wave skeletonization method has been carried out and it shows a good time and qualitative recognition results. Methods: The methods of Zhang-Suen, Hildich and thinning algorithm based on Ateb-Gabor filtration, which form the skeletons of biometric fingerprint images, are considered. The proposed thinning algorithm based on Ateb-Gabor filtration showed better efficiency because it is based on the best type of filtering, which is both a combination of the classic Gabor function and the harmonic Ateb function. The combination of this type of filtration makes it possible to more accurately form the surroundings where the skeleton is formed. Results: Along with the known ones, a new Ateb-Gabor filtering algorithm with the wave skeletonization method has been developed, the recognition results of which have better quality, which allows to increase the recognition quality from 3 to 10%. Conclusion: The Zhang-Suen algorithm is a 2-way algorithm, so for each iteration, it performs two sets of checks during which pixels are removed from the image. Zhang-Suen's algorithm works on a plot of black pixels with eight neighbors. This means that the pixels found along the edges of the image are not analyzed. Hilditch thinning algorithm occurs in several passages, where the algorithm checks all pixels and decides whether to replace a pixel from black to white if certain conditions are satisfied. This Ateb-Gabor filtering will provide better performance, as it allows to obtain more hollow shapes, organize a larger range of curves. Numerous experimental studies confirm the effectiveness of the proposed method.

P‐77: LTPS TDDI with Full‐screen Fingerprint Recognition

2021 ◽  
Vol 52 (1) ◽  
pp. 1368-1371
Author(s):  
Bozhi Liu ◽  
Xuanxian Cai ◽  
Jiaqian Wu ◽  
Xiaoxiao Wu ◽  
Binbin Chen ◽  
...  
Keyword(s):  
Fingerprint Recognition ◽  
Full Screen

P‐74: Large‐Area Optical Fingerprint‐Recognition Scheme under LCD Screen

2021 ◽  
Vol 52 (1) ◽  
pp. 1358-1360
Author(s):  
Xiaowei Ye ◽  
Guangkun Liu ◽  
Zhou Zhang ◽  
Guowei Zha ◽  
Guanghui Liu
Keyword(s):  
Fingerprint Recognition ◽  
Large Area

scholarly journals The Study of Three-Dimensional Fingerprint Recognition in Cultural Heritage

2021 ◽  
Vol 14 (4) ◽  
pp. 1-20
Author(s):  
Dzemila Sero ◽  
Isabelle Garachon ◽  
Erma Hermens ◽  
Robert Van Liere ◽  
Kees Joost Batenburg
Keyword(s):  
Image Processing ◽  
Cultural Heritage ◽  
Three Dimensional ◽  
Fingerprint Recognition ◽  
Person Identification ◽  
Imaging Technologies ◽  
The Past ◽  
Reconstruction Methods ◽  
Cultural Systems ◽  
Digital Fingerprint

Fingerprints play a central role in any field where person identification is required. In forensics and biometrics, three-dimensional fingerprint-based imaging technologies, and corresponding recognition methods, have been vastly investigated. In cultural heritage, preliminary studies provide evidence that the three-dimensional impressions left on objects from the past (ancient fingerprints) are of paramount relevance to understand the socio-cultural systems of former societies, to possibly identify a single producer of multiple potteries, and to authenticate the artist of a sculpture. These findings suggest that the study of ancient fingerprints can be further investigated and open new avenues of research. However, the potential for capturing and analyzing ancient fingerprints is still largely unexplored in the context of cultural heritage research. In fact, most of the existing studies have focused on plane fingerprint representations and commercial software for image processing. Our aim is to outline the opportunities and challenges of digital fingerprint recognition in answering a range of questions in cultural heritage research. Therefore, we summarize the fingerprint-based imaging technologies, reconstruction methods, and analyses used in biometrics that could be beneficial to the study of ancient fingerprints in cultural heritage. In addition, we analyze the works conducted on ancient fingerprints from potteries and ceramic/fired clay sculptures. We conclude with a discussion on the open challenges and future works that could initiate novel strategies for ancient fingerprint acquisition, digitization, and processing within the cultural heritage community.

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